The following data set is information obtained about counties in the United States from 2010 through 2019 through the United States Census Bureau. Information described in the data includes the age distributions, the education levels, employment statistics, ethnicity percents, houseold information, income, and other miscellneous statistics. (Values are denoted as -1, if the data is not available)

Data Dictionary

The percentage of persons, out of the total number of persons living in an area, self-identifying as racially Black or African American (and ethnically non-Hispanic). “Black or African American” refers to a person having origins in any of the Black racial groups of Africa. This indicator includes people who identified their race as “Black”. Source: U.S. Census Bureau, American Community Survey Years Available: 2010, 2011-2015, 2012-2016, 2013-2017, 2014-2018, 2015-2019, 2020, 2017-2021, 2018-2022, 2019-2023

Use this application to view the pattern of concentrations of people by race and Hispanic or Latino ethnicity. Data are provided at the U.S. Census block group level, one of the smallest Census geographies, to provide a detailed picture of these patterns. The data is sourced from the U.S Census Bureau, 2020 Census Redistricting Data (Public Law 94-171) Summary File. Definitions: Definitions of the Census Bureau’s categories are provided below. This interactive map shows patterns for all categories except American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander. The total population countywide for these two categories is small (1,582 and 263 respectively). The Census Bureau uses the following race categories:Population by RaceWhite – A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.Black or African American – A person having origins in any of the Black racial groups of Africa.American Indian or Alaska Native – A person having origins in any of the original peoples of North and South America (including Central America) and who maintains tribal affiliation or community attachment.Asian – A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian subcontinent including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.Native Hawaiian or Other Pacific Islander – A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.Some Other Race - this category is chosen by people who do not identify with any of the categories listed above. People can identify with more than one race. These people are included in the Two or More Races Hispanic or Latino PopulationThe Hispanic/Latino population is an ethnic group. Hispanic/Latino people may be of any race.Other layers provided in this tool included the Loudoun County Census block groups, towns and Dulles airport, and the Loudoun County 2021 aerial imagery.

Context

Percentage of resident persons who declared themselves black in relation to the total resident population, at the reference date of the Demographic Census. Source: IBGE, Demographic Census 2010 and Municipal fabric 2010. http://www.geoservicos.ibge.gov.br/geoserver/wms?service=WFS&version=1.0.0&request=GetFeature&typeName=CGEO:vw_per_black_people& om the dataset summary Population Census and Mesh ... License not specified spatial: "type": "Polygon", "coordinates": [[- [- 74.0046, -33.7411], [- 34.7929, -33.7411], [- 34.7929,5.2727], [- 74.0046,5.2727], [- 74.0046, -33.7411 ]]] http://dados.gov.br/dataset/cgeo_vw_per_pessoas_pretas

Content

Author and Maintainer: Geosciences Directorate - IBGE and Research Directorate - IBGE Last update: June 12, 2018 package id: 4565a7e3-9509-43dc-b074-433451ef7a47 Organ - Sphere: Federal. Organ - Power: Executive.

Acknowledgements

Geosciences Directorate - IBGE and Research Directorate - IBGE http://dados.gov.br

Photo by Anomaly on Unsplash

Inspiration

Nelson Mandela: was a South African anti-apartheid revolutionary, political leader, and philanthropist who served as President of South Africa from 1994 to 1999. He was the country's first black head of state and the first elected in a in a fully representative democratic election. His government focused on dismantling the legacy of apartheid by tackling institutionalized racism and fostering racial reconciliation. https://en.wikipedia.org/wiki/Nelson_Mandela

Martin Luther King Jr. (January 15, 1929 – April 4, 1968) was an American Christian minister and activist who became the most visible spokesperson and leader in the Civil Rights Movement from 1955 until his assassination in 1968. Born in Atlanta Georgia, King is best known for advancing civil rights through nonviolence and civil disobedience, inspired by his Christian beliefs and the nonviolent activism of Mahatma Gandhi. https://en.wikipedia.org/wiki/Martin_Luther_King_Jr.

In 1997 the Population Studies and Training Center (PSTC) of Brown University undertook a series of comparative training and research projects in three countries Vietnam, Ethiopia, and Guatemala. The projects were concerned with the training of planners and researchers in procedures for collecting and analyzing information on migration and its relation to development, women's status, health, and reproduction. Recognizing the importance of migration in South Africa and the pressing need for increasing the number of qualified researchers capable of focussing on this topic, in 1998 the Andrew W. Mellon Foundation provided additional funds to add South Africa to the project. The Centre for Population Studies (CENPOPS) at Pretoria University was given responsibility for the project, working in cooperation with scholars from PSTC at Brown University. The focus of the South African project was on the country's black population. Migration is defined in the survey as movement from one district to another or, if movement is within a district, between a rural and an urban area.

Abstract

Objective The objective of the study is to assess the burden and the spectrum of environmental and genetic determinants of T2D and selected associated microvascular complications in SSA. Methods A multi-national study integrating epidemiological and genomic techniques designed as case-series and population based cross-sectional surveys at 10 sites in 7 countries spanning west, east and southern Africa. Up to 6000 cases of T2D from health facilities and 6000 population based controls will be recruited. This design makes it possible to efficiently draw cases of T2D from health facilities and align them to controls from an appropriate base population while providing an opportunity to estimate prevalence from the survey component of the study. The integrated approach provides a framework for assessing burden, spectrum, and environmental and genetic risk factors for T2D and associated clinical complications.

Geographic coverage

Cameroon, Guinea, Malawi, Nigeria, South Africa, Tanzania, Uganda

Analysis unit

The unit of analysis is the human individual. Each record corresponds to an individual.

Universe

The population in both the survey and clinic arms of the study was of self-identified black Africans, 18 years or older and resident in their respective localities. The inclusion and exclusion criteria are in the table below.

Inclusion and Exclusion criteria

Clinic Arm Inclusion
Age=>25 years. Clinically diagnosed T2D based on data extracted from patient medical records according to current ADA and WHO definitions. Fasting plasma glucose (FPG) =>7.0mmol/ (=>126mg/dl) OR o Two-hours post-load glucose (2h-PG) =>11.1 mmol/l (=>200mg/dl) OR o Symptoms of diabetes and random plasma glucose => 11.1 mmol/l (=200mg/dl) OR o On oral or insulin treatment for diabetes. Individual of African origin (Black) Signed informed consent.

Exclusion · Pregnant women - can participate six months after childbirth · Diabetes classified other than T2D or doubt as to classification · Living outside the geographical sampling frame for the relevant site · Self-defined ethnic group regarded as other than African (Black) · Unable to give informed consent

Survey Arm Inclusion
Resident in the relevant geographical sampling frame Age=>18 years · Individual of African origin (Black) Signed informed consent

Exclusion · Pregnant women - can participate six months after childbirth · Resident outside the relevant geographical sampling frame · Self-defined ethnic group regarded as other than African (Black) · Unable to give informed consent

Kind of data

Includes data on:Socio-demographic, biophysical and anthropometric, biochemical factors as well as fundus image grading.

Sampling procedure

T2D cases were recruited purposively selected from health facilities within the geographical location of study centres using patient registers as sampling frames. Surveys were conducted in the catchment areas of the selected health facilities using a two-stage cluster sampling design involving predefined geographical areas such as administrative units and households. Listings of administrative units and households were obtained from each country's National Statistics Office or equivalent agency, or generated with the help of a local leader of the area to provide a sampling frame.

BackgroundStudies on the barriers migrant women face when trying to access healthcare services in South Africa have emphasized economic factors, fear of deportation, lack of documentation, language barriers, xenophobia, and discrimination in society and in healthcare institutions as factors explaining migrants’ reluctance to seek healthcare. Our study aims to visualize some of the outcome effects of these barriers by analyzing data on maternal death and comparing the local population and black African migrant women from the South African Development Countries (SADC) living in South Africa. The heightened maternal mortality of black migrant women in South Africa can be associated with the hidden costs of barriers migrants face, including xenophobic attitudes experienced at public healthcare institutions.MethodsOur analysis is based on data on reported causes of death (COD) from the South African Department of Home Affairs (DHA). Statistics South Africa (Stats SA) processed the data further and coded the cause of death (COD) according to the WHO classification of disease, ICD10. The dataset is available on the StatsSA website (http://nesstar.statssa.gov.za:8282/webview/) for research and statistical purposes. The entire dataset consists of over 10 million records and about 50 variables of registered deaths that occurred in the country between 1997 and 2018. For our analysis, we have used data from 2002 to 2015, the years for which information on citizenship is reliably included on the death certificate. Corresponding benchmark data, in which nationality is recorded, exists only for a 10% sample from the population and housing census of 2011. Mid-year population estimates (MYPE) also exist but are not disaggregated by nationality. For this reason, certain estimates of death proportions by nationality will be relative and will not correspond to crude death rates.ResultsThe total number of female deaths recorded from the years 2002 to 2015 in the country was 3740.761. Of these, 99.09% (n = 3,707,003) were deaths of South Africans and 0.91% (n = 33,758) were deaths of SADC women citizens. For maternal mortality, we considered the total number of deaths recorded for women between the ages of 15 and 49 years of age and were 1,530,495 deaths. Of these, deaths due to pregnancy-related causes contributed to approximately 1% of deaths. South African women contributed to 17,228 maternal deaths and SADC women to 467 maternal deaths during the period under study. The odds ratio for this comparison was 2.02. In other words, our findings show the odds of a black migrant woman from a SADC country dying of a maternal death were more than twice that of a South African woman. This result is statistically significant as this odds ratio, 2.02, falls within the 95% confidence interval (1.82–2.22).ConclusionThe study is the first to examine and compare maternal death among two groups of women, women from SADC countries and South Africa, based on Stats SA data available for the years 2002–2015. This analysis allows for a better understanding of the differential impact that social determinants of health have on mortality among black migrant women in South Africa and considers access to healthcare as a determinant of health. As we examined maternal death, we inferred that the heightened mortality among black migrant women in South Africa was associated with various determinants of health, such as xenophobic attitudes of healthcare workers toward foreigners during the study period. The negative attitudes of healthcare workers toward migrants have been reported in the literature and the media. Yet, until now, its long-term impact on the health of the foreign population has not been gaged. While a direct association between the heightened death of migrant populations and xenophobia cannot be established in this study, we hope to offer evidence that supports the need to focus on the heightened vulnerability of black migrant women in South Africa. As we argued here, the heightened maternal mortality among migrant women can be considered hidden barriers in which health inequality and the pervasive effects of xenophobia perpetuate the health disparity of SADC migrants in South Africa.

Biological conservation requires a fundamental understanding of evolutionary history and established contemporary population genetics. Here, we sequenced mitochondrial DNA (mtDNA) and thousands of nuclear loci across individuals of the African Black Duck Anas sparsa and Yellow-billed Duck A. undulata to understand the evolutionary histories and to establish their current population structure. In addition to testing for possible hybridisation between these two African species, we compared the genetic ancestries with known wild and domestic Mallards A. platyrhynchos to understand whether the presence of that species in Africa is resulting in elevated interspecific hybridisation. Finally, we assessed morphological variation within the two African species; although the sample sizes limited inferences for the African Black Duck, we were able to demarcate trait cut-offs for field identification of the sexes of the Yellow-billed Duck. We recovered strong population structure between the two species and the Mallard for both mtDNA and nuclear loci. Whereas we recovered high levels of co-ancestry and low levels of nucleotide diversity among the African Black Duck samples, our demographic analysis estimated a contemporary effective population size of ∼2.5 million, which was equivalent to the estimate for the Yellow-billed Duck. We found that the increase in effective population size of both African species coincides with the onset of the last glacial cycle, with numbers peaking during the last glacial maximum. We recovered two genetic hybrids from the samples: a single hybrid between Yellow-billed Duck and wild Mallard, and the first genetically vetted Yellow-billed Duck × African Black Duck hybrid. Our study not only sheds light on the current population structures and standing genetic variation, but outlines methodologies to build morphological cut-offs for species and sex identification, which could be applied in future conservation efforts for Yellow-billed Ducks and African Black Ducks.

HLA Class II Haplotype Frequency Distributions (for 99% haplotypes per population) and HLA Class II Simulated Populations (Genotype level information for sample sizes of 1000, 5000, 10000 simulated individuals) for 4 broad and 21 detailed US population groups.

Broad population groups: African Americans (AFA), Asian and Pacific Islanders (API), Caucasians (CAU), Hispanics (HIS).

Detailed population groups: African American (AAFA), African (AFB), South Asian Indian (AINDI), American Indian - South or Central American (AISC), Alaska native of Aleut (ALANAM), North American Indian (AMIND), Caribbean Black (CARB), Caribbean Hispanic (CARHIS), Caribbean Indian (CARIBI), European Caucasian (EURCAU), Filipino (FILII), Hawaiian or other Pacific Islander (HAWI), Japanese (JAPI), Korean (KORI), Middle Eastern or North Coast of Africa (MENAFC), Mexican or Chicano (MSWHIS), Chinese (NCHI), Hispanic - South or Central American (SCAHIS), Black - South or Central American (SCAMB), Southeast Asian (SCSEAI), Vietnamese (VIET).

Additional file 2. All projections of CSMF accuracy comparing population cause distributions estimated with verbal autopsies of facility deaths to observed population cause distributions from verbal autopsies of community and facility deaths, in four sub-Saharan Africa countries.

Table 2: Density estimates for Black-backed jackals (Lupulella mesomelas) in the grassland habitat on Telperion Nature Reserve from April to June 2017.